Search results for "nanoscale"
showing 10 items of 752 documents
Modelling nanoscale fluid dynamics and transport in physiological flows
1996
The concept of nanotechnology is discussed, and its connection with biomedical engineering is elucidated. For the specific field of nanoscale flow and transport problems of physiological relevance, some typical examples are presented, and their interaction is discussed for some classic biomechanical problems like the flow in arteries with blood-wall coupling. Then, existing computational models are presented and classified according to the length scale of interest, with emphasis on particle-fluid problems. Final remarks address the essential unity of biomedical and engineering behaviour and the possible relevance to small-scale industrial research.
Topology driven g-factor tuning in type-II quantum dots
2017
We investigate how the voltage control of the exciton lateral dipole moment induces a transition from singly to doubly connected topology in type-II InAs/GaAsxSb1−x quantum dots. The latter causes visible Aharonov-Bohm oscillations and a change of the exciton g factor, which are modulated by the applied bias. The results are explained in the frame of realistic →k⋅→p and effective Hamiltonian models and could open a venue for new spin quantum memories beyond the InAs/GaAs realm.
Study of the reactive dynamics of nanometric metallic multilayers using Molecular Dynamics: the Al−Ni system
2012
A molecular dynamics study of a layered Ni-Al-Ni system is developed using an embedded atom method potential. The specific geometry is designed to model a Ni-Al nanometric metallic multilayer. The system is initially thermalized at the fixed temperature of 600 K. We first observe the interdiffusion of Ni and Al at the interfaces, which is followed by the spontaneous phase formation of B2-NiAl in the Al layer. The solid-state reaction is associated with a rapid system's heating which further enhances the diffusion processes. NiAl phase is organized in small regions separated by grain boundaries. This study confirms the hypothesis of a layer-by-layer development of the new phase. For longer t…
Transient dynamics of pulse-driven memristors in the presence of a stable fixed point
2019
Abstract Some memristors are quite interesting from the point of view of dynamical systems. When driven by narrow pulses of alternating polarities, their dynamics has a stable fixed point, which may be useful for future applications. We study the transient dynamics of two types of memristors characterized by a stable fixed point using a time-averaged evolution equation. Time-averaged trajectories of the Biolek window function memristor and resistor-threshold type memristor circuit (an effective memristor) are determined analytically, and the times of relaxation to the stable fixed point are found. Our analytical results are in perfect agreement with the results of numerical simulations.
Perspective on unconventional computing using magnetic skyrmions
2023
Learning and pattern recognition inevitably requires memory of previous events, a feature that conventional CMOS hardware needs to artificially simulate. Dynamical systems naturally provide the memory, complexity, and nonlinearity needed for a plethora of different unconventional computing approaches. In this perspective article, we focus on the unconventional computing concept of reservoir computing and provide an overview of key physical reservoir works reported. We focus on the promising platform of magnetic structures and, in particular, skyrmions, which potentially allow for low-power applications. Moreover, we discuss skyrmion-based implementations of Brownian computing, which has rec…
Modeling Networks of Probabilistic Memristors in SPICE
2021
Efficient simulation of stochastic memristors and their networks requires novel modeling approaches. Utilizing a master equation to find occupation probabilities of network states is a recent major departure from typical memristor modeling [Chaos, solitons fractals 142, 110385 (2021)]. In the present article we show how to implement such master equations in SPICE – a general purpose circuit simulation program. In the case studies we simulate the dynamics of acdriven probabilistic binary and multi-state memristors, and dc-driven networks of probabilistic binary and multi-state memristors. Our SPICE results are in perfect agreement with known analytical solutions. Examples of LTspice code are…
Probabilistic Memristive Networks: Application of a Master Equation to Networks of Binary ReRAM cells
2020
Abstract The possibility of using non-deterministic circuit components has been gaining significant attention in recent years. The modeling and simulation of their circuits require novel approaches, as now the state of a circuit at an arbitrary moment in time cannot be predicted deterministically. Generally, these circuits should be described in terms of probabilities, the circuit variables should be calculated on average, and correlation functions should be used to explore interrelations among the variables. In this paper, we use, for the first time, a master equation to analyze the networks composed of probabilistic binary memristors. Analytical solutions of the master equation for the ca…
Quantum pattern recognition in photonic circuits
2021
This paper proposes a machine learning method to characterize photonic states via a simple optical circuit and data processing of photon number distributions, such as photonic patterns. The input states consist of two coherent states used as references and a two-mode unknown state to be studied. We successfully trained supervised learning algorithms that can predict the degree of entanglement in the two-mode state as well as perform the full tomography of one photonic mode, obtaining satisfactory values in the considered regression metrics.
Supervised Quantum Learning without Measurements
2017
We propose a quantum machine learning algorithm for efficiently solving a class of problems encoded in quantum controlled unitary operations. The central physical mechanism of the protocol is the iteration of a quantum time-delayed equation that introduces feedback in the dynamics and eliminates the necessity of intermediate measurements. The performance of the quantum algorithm is analyzed by comparing the results obtained in numerical simulations with the outcome of classical machine learning methods for the same problem. The use of time-delayed equations enhances the toolbox of the field of quantum machine learning, which may enable unprecedented applications in quantum technologies. The…
Metastable memristive lines for signal transmission and information processing applications
2016
Traditional studies of memristive devices have mainly focused on their applications in nonvolatile information storage and information processing. Here, we demonstrate that the third fundamental component of information technologies-the transfer of information-can also be employed with memristive devices. For this purpose, we introduce a metastable memristive circuit. Combining metastable memristive circuits into a line, one obtains an architecture capable of transferring a signal edge from one space location to another. We emphasize that the suggested metastable memristive lines employ only resistive circuit components. Moreover, their networks (for example, Y-connected lines) have an info…